For improved performance, code can be executed in a distributed fashion in a parallel computing system that has multiple processing nodes. Distributed processing can include dividing processing tasks into multiple partitions that can be concurrently executed by the multiple processing nodes.
In some cases, a specialized framework, library or programming language can be used to implement a distributed processing system. Examples include the MapReduce framework, the MPI (Message Passing Interface) Library, and the Erlang programming language. However, using such specialized frameworks, libraries, and languages involves understanding parallel programming concepts that can be relatively complex.